Awesome stuff. just curious how much of this was written by AI autonomously ?
Show HN: ChartGPU – WebGPU-powered charting library (1M points at 60fps)
151–160 of 226 posts
Re: Show HN: ChartGPU – WebGPU-powered charting library (1M points at 60fps)
#152Earlier quoted context omitted.
Is there any techniques using wavelet decomposition to decimate the high frequency component while retaining peaks? I feel like that's a more principled approach than sampling but I haven't seen any literature on it describing the specific techniques (unless the idea is fundamentally unsound which is not obvious to me).
Interesting idea - I haven't explored wavelet-based approaches but the intuition makes sense: decompose into frequency bands, keep the low-frequency trend, and selectively preserve high-frequency peaks that exceed some threshold. My concern would be computational cost for real-time/streaming use cases. LTTB is O(n) and pretty cache-friendly. Wavelet transforms are more expensive, though maybe a GPU compute shader cou…
I don't. I just remember watching a presentation on it and it always struck me that wavelets are an incredibly powerful and underutilized technique for data reduction while preserving quality in a quantifiable and mathematically justifiable way.
I don't have any papers in mind, but I do think that the critique around visual shape vs signal reconstruction may not be accurate given that wavelets are starting to see a lot of adoption in the visual space (at least JPEG2000 is the leading edge in that field). Might also be interesting to use DCT as well. I think these will perform better than LTTB (of course the compute cost is higher but there's also HW acceleration for some of these or will be over time).
Re: Show HN: ChartGPU – WebGPU-powered charting library (1M points at 60fps)
#153Nice. Add some extras like being able to draw lines (for the candlesticks) and bands. Could just be an add on. The ability not only to plot things, but point them out is a must for me.
I’ve written several of these in the past. Was going to write one in pure WebGPU for a project I’m working on but you beat me to it and now I feel compelled to try yours before going down yet another charting rabbit hole.
Re: Show HN: ChartGPU – WebGPU-powered charting library (1M points at 60fps)
#154uPlot maintainer here. this looks interesting, i'll do a deeper dive soon :) some notes from a very brief look at the 1M demo: - sampling has a risk of eliminating important peaks, uPlot does not do it, so for apples-to-apples perf comparison you have to turn that off. see https://github.com/leeoniya/uPlot/pull/1025 for more details on the drawbacks of LTTB - when doing nothing / idle, there is significant cpu being…
Original Flot maintainer here. I once had to deal with many million data points for an application. I ended up mip-mapping them client-side. But regarding sampling, if it's a line chart, you can sample adaptively by checking whether the next point makes a meaningfully visible difference measured in pixels compared to its neighbours. When you tune it correctly, you can drop most points without the difference being not…
We routinely face this in the audio world when drawing waveforms. You typically have on the order of 10-100k samples per second, durations of 10s-1000s of seconds, and pixel widths of on the order of 1-10k pixels.
Bresenham's is one algorithm historically used to downsample the data, but a lot of contemporary audio software doesn't use that. In Ardour (a cross-platform, libre, open source DAW), we actually compute and store min/max-per-N-samples and use that for plotting (and as the basis for further downsampling.
Re: Show HN: ChartGPU – WebGPU-powered charting library (1M points at 60fps)
#155Impressive! Most impressive.
Re: Show HN: ChartGPU – WebGPU-powered charting library (1M points at 60fps)
#156Right on time. We’ve been working on a browser-based Link Graph (osint) analysis tool for months now ( https://webvetted.com/workbench ). The graph charting tools on the market are pretty basic for the kind of charting we are looking to do (think 1000s of connected/disconnected nodes/edges. Being able to handle 1M points is a dream. This will come in very handy.
Does Cosmos.gl do what you need? https://cosmos.gl/?path=/docs/welcome-to-cosmos-gl--docs
Re: Show HN: ChartGPU – WebGPU-powered charting library (1M points at 60fps)
#157Earlier quoted context omitted.
Original Flot maintainer here. I once had to deal with many million data points for an application. I ended up mip-mapping them client-side. But regarding sampling, if it's a line chart, you can sample adaptively by checking whether the next point makes a meaningfully visible difference measured in pixels compared to its neighbours. When you tune it correctly, you can drop most points without the difference being not…
We routinely face this in the audio world when drawing waveforms. You typically have on the order of 10-100k samples per second, durations of 10s-1000s of seconds, and pixel widths of on the order of 1-10k pixels. Bresenham's is one algorithm historically used to downsample the data, but a lot of contemporary audio software doesn't use that. In Ardour (a cross-platform, libre, open source DAW), we actually compute an…
> In Ardour (a cross-platform, libre, open source DAW), we actually compute and store min/max-per-N-samples and use that for plotting (and as the basis for further downsampling.
this is, effectively, what uPlot does, too: https://github.com/leeoniya/uPlot/issues/1119
Re: Show HN: ChartGPU – WebGPU-powered charting library (1M points at 60fps)
#158uPlot maintainer here. this looks interesting, i'll do a deeper dive soon :) some notes from a very brief look at the 1M demo: - sampling has a risk of eliminating important peaks, uPlot does not do it, so for apples-to-apples perf comparison you have to turn that off. see https://github.com/leeoniya/uPlot/pull/1025 for more details on the drawbacks of LTTB - when doing nothing / idle, there is significant cpu being…
Original Flot maintainer here. I once had to deal with many million data points for an application. I ended up mip-mapping them client-side. But regarding sampling, if it's a line chart, you can sample adaptively by checking whether the next point makes a meaningfully visible difference measured in pixels compared to its neighbours. When you tune it correctly, you can drop most points without the difference being not…
hey!
> But regarding sampling, if it's a line chart, you can sample adaptively by checking whether the next point makes a meaningfully visible difference measured in pixels compared to its neighbours.
uPlot basically does this (see sibling comment), so hopefully that's some validation for you :)
Re: Show HN: ChartGPU – WebGPU-powered charting library (1M points at 60fps)
#159Right on time. We’ve been working on a browser-based Link Graph (osint) analysis tool for months now ( https://webvetted.com/workbench ). The graph charting tools on the market are pretty basic for the kind of charting we are looking to do (think 1000s of connected/disconnected nodes/edges. Being able to handle 1M points is a dream. This will come in very handy.
You may enjoy Graphistry (eg, pygraphistry, GraphistryJS), where our users regularly do 1M+ graph elements interactively, such as for event & entity data. Webgl frontend, GPU server backend for layouts too intense for frontend. We have been working on stability over the last year with large-scale rollout users (esp cyber, IT, social, finance, and supply chain), and now working on the next 10X+ of visual scaling. Python version: https://github.com/graphistry/pygraphistry . It includes many of the various tricks mentioned here, like GPU hitmapping, and we helped build various popular libs like apache arrow for making this work end-to-end :)
Most recently adding to the family is our open source GFQL graph language & engine layer (cypher on GPUs, including various dataframe & binary format support for fast & easy large data loading), and under the louie.ai umbrella, piloting genAI extensions
Re: Show HN: ChartGPU – WebGPU-powered charting library (1M points at 60fps)
#160uPlot maintainer here. this looks interesting, i'll do a deeper dive soon :) some notes from a very brief look at the 1M demo: - sampling has a risk of eliminating important peaks, uPlot does not do it, so for apples-to-apples perf comparison you have to turn that off. see https://github.com/leeoniya/uPlot/pull/1025 for more details on the drawbacks of LTTB - when doing nothing / idle, there is significant cpu being…
I wouldn't spend too much of your time deep diving - it's an AI slop project.